
import onnxruntime as rt
import numpy as np

sess = rt.InferenceSession("modified_model.onnx")
input_data = np.random.randn(1, 3, 300, 480).astype(np.float32)  # 示例输入
output = sess.run(None, {'input': input_data})[0]
print(output.shape)  # 应为 (1, 19, H, W) 而非 (1, 1, H, W)
